Insourcing vs Outsourcing: Rethinking the Data Team for SMBs

For SMBs, building a data capability used to mean one thing. Hiring a full in-house team of data wizards that brought together varying skills from across the data landscape. But with rising salaries, growing tech complexity, and an increasing need for funding flexibility, many businesses are rethinking that approach. The question now isn’t whether you need data expertise because that is a given. It is whether you need it in-house.

What Does a Typical In-House Data Team Cost?

Let’s take an Australian business with around 200 staff. To support reporting, data infrastructure, and decision-making, a typical (and perhaps conservative) internal setup might include:

Data Architect $165,000

Data Engineer $135,000

Data Scientist $115,000

BI Analyst $100,000

Total Cost: $500,000 per year

This is purely headcount cost according to seek.com.au. Just to be crystal clear, this doesn’t include:

• Recruitment

• Onboarding

• Licences and tools

• Ongoing management and professional development

• Time lost to under-utilisation or misalignment

  
  

For many SMBs, this is a steep price to pay, especially if data isn’t yet central to day-to-day operations. But, if you are putting this in the too-hard-basket, I have some good news. Keep reading. There are cheaper and better ways to get the desired insights you need to grow your business, without the half-million dollar price tag.

What Are the Alternatives?

Instead of hiring a permanent team, businesses are increasingly turning to outsourced or fractional data services. These might include:

• Data strategy consulting

• On-demand engineering and architecture support

• Fully-managed analytics services (like Pentify Insights Data-as-a-Service)

• Part-time leadership (e.g. a fractional CDO or Head of Data)

  
  

These models allow businesses to access specialist skills without the commitment of a full internal team, for considerably less.

Why Outsourcing Can Make More Sense

1. Cost Efficiency

Outsourcing lets you pay only for what you need. Whether that’s 4 days a month or a 12-week project. It avoids the overheads of full-time hires ($500k!!)

2. Speed

External experts can often move faster, with less ramp-up time and less internal friction. That means quicker access to insights, better decisions, and better business outcomes.

3. Access to Broader Skillsets

One of the challenges of a small in-house team is skill coverage. Outsourced providers typically bring a blend of architecture, engineering, analytics, and governance expertise.

4. Flexibility and Scalability

Your data needs will grow, but not always consistently. Outsourcing gives you the ability to scale support up or down as your priorities shift.

5. Strategic Alignment

External data partners tend to focus more on business outcomes and ROI, not just delivery. That means your reporting and infrastructure are more likely to stay aligned to the commercial goals of the business.

When In-House Makes Sense

To be clear, insourcing still has its place. For businesses with:

• A large, stable stream of internal data projects

• Complex data workflows tied closely to operational systems

• High levels of regulatory oversight or sensitivity

  
  

it can still make sense to invest in a dedicated internal team. But for many others, especially those still thinking about data or are slightly more advanced in building their foundations, outsourcing is a faster, leaner, and more adaptable way to scale.

Good data is now essential for decision-making. Whether that is to understand what has happened in the traditional reporting sense, or if you are looking to dip the toe into the world of automation and AI, good data is the foundation of it all. But, and it is a big but, that doesn’t mean every business needs to hire an expensive, multi-person team to get started. There are better ways! For SMBs, outsourcing offers a way to de-risk the investment, accelerate delivery, and ensure your data capability grows in line with your actual needs.